المحتوى المقدم من Medical Attention. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Medical Attention أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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I think you could probably go back and track the stages of grief, probably that is what I went through. But I think if you do it right, you end up at acceptance. And that's where I ended up. And that's not to say that I've fully accepted the idea that the golden toad is extinct. Personally, I do still hold out hope that it could still be out there in those forests." - Trevor Ritland This conversation is with Trevor Ritland, who—along with his twin brother Kyle—authored The Golden Toad . The book chronicles their remarkable journey into Costa Rica’s cloud forest, once home to hundreds of brilliant golden toads that would emerge for just a few weeks each year—until, one day, they vanished without a trace. What began as a search for a lost species soon became something much more profound: a confrontation with ecological grief, a meditation on hope, and a powerful call to protect the natural world while we still can. Links: SpeciesUnite.com Kyle and Trevor: https://kyleandtrevor.com/ Instagram: https://www.instagram.com/adventureterm/ Goodreads - https://www.goodreads.com/book/show/222249677-the-golden-toad Amazon - https://www.amazon.com/Golden-Toad-Ecological-Mystery-Species/dp/163576996…
المحتوى المقدم من Medical Attention. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Medical Attention أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Medical attention is a podcast about artificial intelligence (AI) in medicine for busy people working in health. We bring you clinically relevant updates from the world of AI so you know how it will impact your patients and work.
المحتوى المقدم من Medical Attention. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة Medical Attention أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
Medical attention is a podcast about artificial intelligence (AI) in medicine for busy people working in health. We bring you clinically relevant updates from the world of AI so you know how it will impact your patients and work.
In this episode, we’re lucky to be joined by Alexandre Sallinen and Tony O’Halloran from the Laboratory for Intelligent Global Health & Humanitarian Response Technologies to discuss how large language models are assessed, including their Massive Open Online Validation & Evaluation (MOOVE) initiative. 0:25 - Technical wrap: what are agents? 13:20 - What are benchmarks? 18:20 - Automated evaluation 20:10 - Benchmarks 37:45 - Human feedback 44:50 - LLM as judge Read more about the projects we discuss here: Meditron Learn about the MOOVE or contact our team if you'd like to be involved Listen to the LiGHTCAST including their recent excellent outline of the HealthBench paper More details in the show notes on our website. Episodes | Bluesky | info@medicalattention.ai…
Here’s a quick wrap of the three papers we found interesting over the last few weeks with some take home points. 0:35 - Superhuman performance of a large language model on the reasoning tasks of a physician 06:20 - MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks 11:45 - Identifying and mitigating algorithmic bias in the safety net More details in the show notes on our website. Episodes | Bluesky | info@medicalattention.ai…
We’re trying out a new episode format! We’ll be doing a quick wrap of the top three papers we found interesting over the last few weeks with some take home points. 01:30 - Patient Reactions to Artificial Intelligence-Clinician Discrepancies 06:50 - AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans for mortality prediction 11:10 - Large-scale Local Deployment of DeepSeek-R1 in Pilot Hospitals in China More details in the show notes on our website. Episodes | Bluesky | info@medicalattention.ai…
In this episode, we tackle some common myths about how generative AI works, why this is the case, implications for healthcare and some quick fixes. These myths include 1) that LLMs can explain their reasoning 2) that LLMs can express uncertainty, 3) that LLMs can a) do maths, b) manage temporal data c) apply guidelines d) handle negation and finally that 4) that AI will replace clinicians. 02:00 Technical update - DeepSeek, other new models 10:00 - AI mybusting 15:50 - LLMs can explain their reasoning 21:50 - LLMs can express uncertainty 26:40 - LLM blindspots 41:50 - AI will replace clinicians Episodes | Bluesky | info@medicalattention.ai…
In this episode, we discuss algorithmic bias and fairness in healthcare. We explain what this is, the different definitions of “fairness”, explore the ways in which bias can enter the machine learning pipeline and some ways to combat it. 01:00 Technical update - NeurIPS 06:50 Technical update - ChatGPT-o3 14:00 - Algorithmic bias Episodes | Bluesky | info@medicalattention.ai…
We’ve returned after an accidental hiatus, just in time for the end of the year. In this episode, we’re joined by the team behind the American Medical Informatics Association (AMIA) Year in Review - Professor James Cimino, Pushkala Jayaraman and Dr Humayera Islam to talk about the main themes in healthcare AI for 2024. 01:00 Technical update (ChatGPT-o1, agentic AI) 10:25 AMIA Year in Review Episodes | Bluesky | info@medicalattention.ai…
We’re back! This is the start of our regular discussions about healthcare AI topics and recent literature. On today’s episode - the 10 commandments of decision support, the checkered history of EMRs, clinicians as “moral crumple zone” for AI models and much more. 01:18 Technical update (Llama 3.1, Phi releases) 06:25 Main discussion 41:20 Article round-up Episodes | Twitter | info@medicalattention.ai…
In this episode, we discuss more of the technical aspects of LLM implementation in healthcare, including the following topics: Embeddings Retrieval augmented generation (RAG) Fine tuning Low-Rank Adaptation (LoRA) Small models Quantisation Encoder and decoder models Multimodal transformers Oh my! Episodes | Twitter | info@medicalattention.ai…
In this episode, we discuss some concerns about LLM implementation in the healthcare setting, including the following topics: More detail about hallucinations, issues with accuracy Difficulties of model evaluation Concerns regarding bias and equity Governance and monitoring of LLMs in a healthcare settings Episodes | Twitter | info@medicalattention.ai…
Finally! We’re talking about large language models (LLMs) including ChatGPT. We discuss the following topics: Brief explanation of transformer models and how they work including the attention mechanism and context window Discuss a brief development of LLMs to this point How LLMs are trained Some limitations - privacy, accuracy, provenance Episodes | Twitter | info@medicalattention.ai…
In this episodes we give an overview of neural networks and how they’re used in healthcare. We'll be covering the following topics: Definition of neural networks and a high level explanation of their structure Overview of the development of neural networks and use in healthcare How neural networks are currently used in medicine Limitations and considerations for their use Episodes | Twitter | info@medicalattention.ai…
Welcome to Medical Attention. This episode is an introduction to artificial intelligence and machine learning for people in healthcare with no technical background. Episodes | Twitter | info@medicalattention.ai
مرحبًا بك في مشغل أف ام!
يقوم برنامج مشغل أف أم بمسح الويب للحصول على بودكاست عالية الجودة لتستمتع بها الآن. إنه أفضل تطبيق بودكاست ويعمل على أجهزة اندرويد والأيفون والويب. قم بالتسجيل لمزامنة الاشتراكات عبر الأجهزة.